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QUASAR: Quantitative Attack Space Analysis and Reasoning

Published: 04 December 2017 Publication History

Abstract

Computer security has long been an arms race between attacks and defenses. While new defenses are proposed and built to stop specific vectors of attacks, novel, sophisticated attacks are devised by attackers to bypass them. This rapid cycle of defenses and attacks has made it difficult to strategically reason about the protection offered by each defensive technique, the coverage of a set of defenses, and possible new vectors of attack for which to design future defenses. In this work, we present QUASAR, a framework that systematically analyzes attacks and defenses at the granularity of the capabilities necessary to mount the attacks. We build a model of attacks in the memory corruption domain, and represent various prominent defenses in this domain. We demonstrate that QUASAR can be used to compare defenses at a fundamental level (what they do instead of how they do it), reason about the coverage of a defensive configuration, and hypothesize about possible new attack strategies. We show that of the top five hypothesized new attack strategies, in fact, four have been published in security venues over the past two years. We investigate the fifth hypothesized vector ourselves and demonstrate that it is, in fact, a viable vector of attack.

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  • (2021)BUCEPHALUS: a BUsiness CEntric cybersecurity Platform for proActive anaLysis Using visual analyticS2021 IEEE Symposium on Visualization for Cyber Security (VizSec)10.1109/VizSec53666.2021.00007(15-25)Online publication date: Oct-2021
  • (2018)Vulnus: Visual Vulnerability Analysis for Network SecurityIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2018.286502825:1(183-192)Online publication date: 7-Dec-2018

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cover image ACM Other conferences
ACSAC '17: Proceedings of the 33rd Annual Computer Security Applications Conference
December 2017
618 pages
ISBN:9781450353458
DOI:10.1145/3134600
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 04 December 2017

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View all
  • (2021)BUCEPHALUS: a BUsiness CEntric cybersecurity Platform for proActive anaLysis Using visual analyticS2021 IEEE Symposium on Visualization for Cyber Security (VizSec)10.1109/VizSec53666.2021.00007(15-25)Online publication date: Oct-2021
  • (2018)Vulnus: Visual Vulnerability Analysis for Network SecurityIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2018.286502825:1(183-192)Online publication date: 7-Dec-2018

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